Senior Engineering Manager
Islamabad · Working globallyI’m Moiz. I architect agentic AI systems and lead the teams bringing them to production, with a background in building and scaling web products.
How I work / Every day
On larger coding tasks I pair Claude Code and Codex. Claude Code writes the code. Codex reads the codebase before the build and reviews the result after, in a fresh context each time.
I engineered the harness around them: what each agent is told, what it can’t do, how its work is checked and how it gets corrected. Decisions the spec doesn’t cover come back to me.
Read the case studySimplified, but the roles, files and rules are how I work.
01 Selected work
A few projects where technical decisions
made a meaningful difference.
01 AI engineering · In production
AI that finds the forms a regulatory change affects, drafts and checks the edits, and hands them to experts to decide.
02 Product architecture · Technical leadership
A website relaunched in under 30 days, then grew into a community platform serving five schools. Built for a deadline, designed for what came next.
03 Full-stack engineering · Infrastructure
Real-time multiplayer escape rooms, a custom video streaming pipeline, and ownership from prototype through production.
04 Frontend systems · Developer experience
An initial marketing launch, followed by longer-term website, tooling and design system work across an 18-month engagement.
02 How I work
I’m a Senior Engineering Manager at Tintash. I stay hands-on while helping teams make good decisions, grow their craft, and take ownership of what they ship.
More about meDeadlines, security, cost, and the team who will maintain it. The right architecture starts with understanding the problem.
Architecture reviews, implementation, and production debugging. Leadership works better when it is grounded in the details.
Clear expectations, thoughtful feedback, and room to take ownership. Strong systems need people who can move them forward.
03 How I lead
Most of what I believe about leading engineers I’ve written down for my teams. Here’s the short version.
I wrote a guide for engineers early in their careers, built around six pillars. Each one pairs a core lesson with a question to sit with.
If you can’t explain the code the AI wrote, don’t commit it.
The goal in year one isn’t to know everything. It’s to learn how to learn: work at the edge of your ability, get feedback, adjust. Three years of the same work is one year repeated three times.
What did you learn this week that was at the edge of your ability?
Reasoning from first principles and an instinct for learning, over depth of knowledge.
Trade-off thinking that shows up unprompted, not tools named from memory.
Systems over heroics, ownership of outcomes, and honesty about what they don’t know.
The conversation about someone’s career and the decision about which project they join need different tools, for different audiences.
Choose the statement that matches how someone typically works. The number follows from that, so nobody can work backwards from a score they already had in mind.
Two people with the same overall score can be opposite fits for the same project. The project decides which strengths matter.
04 The workshop
Smaller tools, experiments,
and things built to learn.
Lighthouse findings, investigated against the actual source code with Claude.
Pakistan Stock Exchange data, available directly to AI assistants.
Exploring reactivity, dependency tracking, and the virtual DOM by building them.
A mock exam and study guide for Claude Certified Architect Foundations.
05
The Pixelated View
Notes on engineering, leadership, and what changes when AI becomes part of the way we work.
Have something in mind?
